Branch threading in graph databases

ABSTRACT

The disclosed embodiments provide a system for processing queries of a graph database storing a graph, wherein the graph comprises a set of edges defined by a first linkage, a second linkage, and a third linkage. During operation, the system maintains the base version of an index of the graph database. Upon branching a version of the graph database from a first offset representing a virtual time in the base version of the graph database, the system creates a branched version of the index from a second offset corresponding to the virtual time in the base version of the index. The system then processes queries of the graph database based on the offsets and references from the branched version of the index to the base version of the index.

BACKGROUND Field

The disclosed embodiments relate to graph databases. More specifically,the disclosed embodiments relate to branch threading in graph databases.

Related Art

Data associated with applications is often organized and stored indatabases. For example, in a relational database data is organized basedon a relational model into one or more tables of rows and columns, inwhich the rows represent instances of types of data entities and thecolumns represent associated values. Information can be extracted from arelational database using queries expressed in a Structured QueryLanguage (SQL).

In principle, by linking or associating the rows in different tables,complicated relationships can be represented in a relational database.In practice, extracting such complicated relationships usually entailsperforming a set of queries and then determining the intersection of theresults or joining the results. In general, by leveraging knowledge ofthe underlying relational model, the set of queries can be identifiedand then performed in an optimal manner

However, applications often do not know the relational model in arelational database. Instead, from an application perspective, data isusually viewed as a hierarchy of objects in memory with associatedpointers. Consequently, many applications generate queries in apiecemeal manner, which can make it difficult to identify or perform aset of queries on a relational database in an optimal manner. This candegrade performance and the user experience when using applications.

Various approaches have been used in an attempt to address this problem,including using an object-relational mapper, so that an applicationeffectively has an understanding or knowledge about the relational modelin a relational database. However, it is often difficult to generate andto maintain the object-relational mapper, especially for large,real-time applications.

Alternatively, a key-value store (such as a NoSQL database) may be usedinstead of a relational database. A key-value store may include acollection of objects or records and associated fields with values ofthe records. Data in a key-value store may be stored or retrieved usinga key that uniquely identifies a record. By avoiding the use of apredefined relational model, a key-value store may allow applications toaccess data as objects in memory with associated pointers (i.e., in amanner consistent with the application's perspective). However, theabsence of a relational model means that it can be difficult to optimizea key-value store. Consequently, it can also be difficult to extractcomplicated relationships from a key-value store (e.g., it may requiremultiple queries), which can also degrade performance and the userexperience when using applications.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a schematic of a system in accordance with the disclosedembodiments.

FIG. 2 shows a graph in a graph database in accordance with thedisclosed embodiments.

FIG. 3 shows a system for processing queries of a graph database inaccordance with the disclosed embodiments.

FIG. 4A shows an example base version and branched version of a graphdatabase in accordance with the disclosed embodiments.

FIG. 4B shows an example base version and branched version of a graphdatabase in accordance with the disclosed embodiments.

FIG. 5 shows a flowchart illustrating a process of providing a graphdatabase storing a graph in accordance with the disclosed embodiments.

FIG. 6 shows a flowchart illustrating the processing of queries of agraph database in accordance with the disclosed embodiments.

FIG. 7 shows a flowchart illustrating the processing of queries of agraph database in accordance with the disclosed embodiments.

FIG. 8 shows a computer system in accordance with the disclosedembodiments.

In the figures, like reference numerals refer to the same figureelements.

DETAILED DESCRIPTION

The following description is presented to enable any person skilled inthe art to make and use the embodiments, and is provided in the contextof a particular application and its requirements. Various modificationsto the disclosed embodiments will be readily apparent to those skilledin the art, and the general principles defined herein may be applied toother embodiments and applications without departing from the spirit andscope of the present disclosure. Thus, the present invention is notlimited to the embodiments shown, but is to be accorded the widest scopeconsistent with the principles and features disclosed herein.

Overview

The disclosed embodiments provide a method, apparatus, and system forprocessing queries of a graph database. In these embodiments, a graphdatabase stores a graph that includes a set of nodes and edges betweenpairs of the nodes. For example, nodes in the graph represent members,organizations, locations, jobs, content, and/or other entities in anonline network. Edges between the nodes represent relationships and/orinteractions between the corresponding entities, such as connectionsbetween pairs of members, education of members at schools, employment ofmembers at companies, following of a member or company by anothermember, business relationships and/or partnerships betweenorganizations, residence of members at locations, creating or sharingarticles or posts, sending and receiving messages, sending or acceptingconnection requests, endorsements or recommendations between members,reviews by the members, applying to opportunities, joining groups,and/or following other entities.

In some embodiments, each edge between two nodes is represented in thegraph database as a first linkage, a second, linkage, and a thirdlinkage. For example, each edge in the graph database is specified in a(subject, predicate, object) triple, with the subject and objectdenoting nodes in the graph database and the predicate denoting the typeof edge between the nodes. Thus, an edge with a subject of “Alice,” apredicate of “connected to,” and an object of “Bob” represents aconnection between two members named “Alice” and “Bob” in an onlinenetwork.

More specifically, the disclosed embodiments provide a method,apparatus, and system for performing branch threading in graphdatabases. In some embodiments, multiple versions of a graph databaseare represented using a tree-based structure. The structure includes abase version or “trunk,” as well as one or more child versions that“branch” off the base version and/or other child versions. When data(e.g., nodes, edges, predicates, etc.) is written to a branched versionof the graph database, the data is stored in a set of structures for thebranched version, which is separate from a corresponding set ofstructures for the base version from which the branched version wascreated. These structures include a log containing a sequence of changesin the graph, with each change represented by an offset in the log thatdenotes a virtual time in the graph. The structures also include anindex that expedites lookup of edges in the graph by subject, predicate,object, and/or other keys. The index includes one or more hash maps thatstore mappings of the keys to offsets into an edge store. The edge storeincludes a number of linkage structures that store additional linkagevalues that can be used to resolve edges associated with the keys in thehash maps.

When a version of the graph database is branched off a given offset inthe log of a base version of the graph database, the offset in the logis stored as a representation of the virtual time at which the branchedversion was created. Offsets of the hash maps and linkage structurescorresponding to the virtual time in the base version of the index aresimilarly stored to indicate the boundary between data in the baseversion that can be read by the branched version and data written thebase version after creation of the branched version, which cannot beread by the branched version.

To allow lookup of data in a branched version of the graph database,references are stored between linkage structures in the edge store inthe branched version and the corresponding linkage structures in thebase version of the graph database from which the branched version wascreated. For example, the base version of the graph database indexincludes a key in a hash map that maps to one or more linkage structuresin the edge store that store remaining linkages for edges that arepartially defined by the key. When a version of the graph database issubsequently branched off the base version and a new edge that includesthe key is written to the branched version, a new entry for the key iscreated in a hash map for the branched version. The entry is updatedwith a mapping of the key to one or more linkage structures in the edgestore for the branched version, and additional linkages that are used toresolve the edge are stored in the linkage structure(s). Each linkagestructure is additionally updated to include a reference to thecorresponding linkage structure in the base version of the edge store,so that subsequent reads of edges associated with the key in thebranched version are able to access edges that were written to the graphdatabase in the base version before the branched version was created.

As a result, branched versions of the graph database represent variantsor alternative versions of the graph that can be created, modified,and/or deleted without affecting the corresponding base versions. Inturn, the branched versions can be used to perform and validate writesto the graph database before merging the writes into the base version,which improves the integrity of data in the graph database and allowsthe validated writes to be applied in an atomic and consistent mannerThe branched versions can also be used to test changes to the data,schema, and/or querying of the graph database without modifying a sourceof truth for the graph in the base versions, which reduces risk,potential for errors or failures, and/or processing overhead associatedwith conventional techniques that deploy changes to the schema, data,and/or querying in databases without testing or validating the changesfirst. Moreover, storing a single copy of data in a base version andusing the data to perform reads of a version that is branched off thebase version reduces the use of storage and/or memory resources in thegraph database. Consequently, the disclosed embodiments providetechnological improvements in applications, tools, computer systems,and/or environments for storing, querying, duplicating, testing,validating, creating, and/or modifying data and/or databases.

Branch Threading in Graph Databases

FIG. 1 shows a schematic of a system 100 in accordance with thedisclosed embodiments. In this system, users of electronic devices 110use a service that is provided, at least in part, using one or moresoftware products or applications executing in system 100. As describedfurther below, the applications are executed by engines in system 100.

Moreover, the service is provided, at least in part, using instances ofa software application that is resident on and that executes onelectronic devices 110. In some implementations, the users interact witha web page that is provided by communication server 114 via network 112,and which is rendered by web browsers on electronic devices 110. Forexample, at least a portion of the software application executing onelectronic devices 110 includes an application tool that is embedded inthe web page, and that executes in a virtual environment of the webbrowsers. Thus, the application tool is provided to the users via aclient-server architecture.

The software application operated by the users includes a standaloneapplication or a portion of another application that is resident on andthat executes on electronic devices 110 (such as a software applicationthat is provided by communication server 114 or that is installed on andthat executes on electronic devices 110).

A wide variety of services can be provided using system 100. In thediscussion that follows, a social network (and, more generally, a usercommunity), such as an online professional network, which facilitatesinteractions among the users, is used as an illustrative example.Moreover, using one of electronic devices 110 (such as electronic device110-1) as an illustrative example, a user of an electronic device usesthe software application and one or more of the applications executed byengines in system 100 to interact with other users in the socialnetwork. For example, administrator engine 118 handles user accounts anduser profiles, activity engine 120 tracks and aggregate user behaviorsover time in the social network, content engine 122 receivesuser-provided content (audio, video, text, graphics, multimedia content,verbal, written, and/or recorded information) and provides documents(such as presentations, spreadsheets, word-processing documents, webpages, etc.) to users, and storage system 124 maintains data structuresin a computer-readable memory that encompasses multiple devices, i.e., alarge-scale storage system.

Note that each of the users of the social network have an associateduser profile that includes personal and professional characteristics andexperiences, which are sometimes collectively referred to as‘attributes’ or ‘characteristics.’ For example, a user profile includes:demographic information (such as age and gender), geographic location,work industry for a current employer, an employment start date, anoptional employment end date, a functional area (e.g., engineering,sales, consulting), seniority in an organization, employer size,education (such as schools attended and degrees earned), employmenthistory (such as previous employers and the current employer),professional development, interest segments, groups that the user isaffiliated with or that the user tracks or follows, a job title,additional professional attributes (such as skills), and/or inferredattributes (which may include or be based on user behaviors). Moreover,user behaviors include: log-in frequencies, search frequencies, searchtopics, browsing certain web pages, locations (such as IP addresses)associated with the users, advertising or recommendations presented tothe users, user responses to the advertising or recommendations, likesor shares exchanged by the users, interest segments for the likes orshares, and/or a history of user activities when using the socialnetwork.

Furthermore, the interactions among the users help define a social graphin which nodes correspond to the users and edges between the nodescorrespond to the users' interactions, interrelationships, and/orconnections. However, as described further below, the nodes in the graphstored in the graph database can correspond to additional or differentinformation than the members of the social network (such as users,companies, etc.). For example, the nodes may correspond to attributes,properties or characteristics of the users.

It can be difficult for the applications to store and retrieve data inexisting databases in storage system 124 because the applications maynot have access to the relational model associated with a particularrelational database (which is sometimes referred to as an‘object-relational impedance mismatch’). Moreover, if the applicationstreat a relational database or key-value store as a hierarchy of objectsin memory with associated pointers, queries executed against theexisting databases may not be performed in an optimal manner.

For example, when an application requests data associated with acomplicated relationship (which may involve two or more edges, and whichis sometimes referred to as a ‘compound relationship’), a set of queriesare performed and then the results may be linked or joined. Toillustrate this problem, rendering a web page for a blog may involve afirst query for the three-most-recent blog posts, a second query for anyassociated comments, and a third query for information regarding theauthors of the comments. Because the set of queries may be suboptimal,obtaining the results can, therefore, be time-consuming. This degradedperformance can degrade the user experience when using the applicationsand/or the social network.

In order to address these problems, storage system 124 includes a graphdatabase that stores a graph (e.g., as part of aninformation-storage-and-retrieval system or engine). Note that the graphallows an arbitrarily accurate data model to be obtained for data thatinvolves fast joining (such as for a complicated relationship with skewor large ‘fan-out’ in storage system 124), which approximates the speedof a pointer to a memory location (and thus may be well suited to theapproach used by applications).

FIG. 2 presents a block diagram illustrating a graph 210 stored in agraph database 200 in system 100 (FIG. 1). Graph 210 includes nodes 212and edges 214 between nodes 212 to represent and store the data withindex-free adjacency, i.e., so that each node 212 in graph 210 includesa direct edge to its adjacent nodes without using an index lookup.

In one or more embodiments, graph database 200 includes animplementation of a relational model with constant-time navigation,i.e., independent of the size N, as opposed to varying as log(N).Moreover, all the relationships in graph database 200 are first class(i.e., equal). In contrast, in a relational database, rows in a tablemay be first class, but a relationship that involves joining tables maybe second class. Furthermore, a schema change in graph database 200(such as the equivalent to adding or deleting a column in a relationaldatabase) is performed with constant time (in a relational database,changing the schema can be problematic because it is often embedded inassociated applications). Additionally, for graph database 200, theresult of a query includes a subset of graph 210 that preserves thestructure (i.e., nodes, edges) of the subset of graph 210.

The graph-storage technique includes embodiments of methods that allowthe data associated with the applications and/or the social network tobe efficiently stored and retrieved from graph database 200. Suchmethods are described in U.S. Pat. No. 9,535,963 (issued 3 Jan. 2017),entitled “Graph-Based Queries,” which is incorporated herein byreference.

Referring back to FIG. 1, the graph-storage techniques described hereinallow system 100 to efficiently and quickly (e.g., optimally) store andretrieve data associated with the applications and the social networkwithout requiring the applications to have knowledge of a relationalmodel implemented in graph database 200. Consequently, the graph-storagetechniques improve the availability and the performance or functioningof the applications, the social network and system 100, which reduceuser frustration and improve the user experience. Therefore, thegraph-storage techniques further increase engagement with or use of thesocial network and, in turn, the revenue of a provider of the socialnetwork.

Note that information in system 100 may be stored at one or morelocations (i.e., locally and/or remotely). Moreover, because this datamay be sensitive in nature, it may be encrypted. For example, storeddata and/or data communicated via networks 112 and/or 116 may beencrypted.

In one or more embodiments, graph database 200 includes functionality toprocess queries using a base version of graph database 200 and/or one ormore versions that are branched off the base version or other branchedversions. As shown in FIG. 3, graph 210 and one or more schemas 306associated with graph 210 are obtained from a source of truth 334 forgraph database 200. For example, graph 210 and schemas 306 may beretrieved from a relational database, distributed filesystem, and/orother storage mechanism providing the source of truth.

As mentioned above, graph 210 includes a set of nodes 316, a set ofedges 318 between pairs of nodes 316, and a set of predicates 320describing the nodes and/or edges. Each edge in graph 210 may bespecified in a (subject, predicate, object) triple. Each component ofthe triple (i.e., subject, predicate, and object) denotes a separate“linkage” that partially defines the edge.

For example, an edge denoting a connection between two members named“Alice” and “Bob” may be specified using the following statement:

-   -   Edge(“Alice”, “ConnectedTo”, “Bob”).        In the above statement, “Alice” is the subject, “Bob” is the        object, and “ConnectedTo” is the predicate. A period following        the “Edge” statement may denote an assertion that is used to        write the edge to graph database 200. Conversely, the period may        be replaced with a question mark to read any edges that match        the subject, predicate, and object from the graph database:    -   Edge(“Alice”, “ConnectedTo”, “Bob”)?        Moreover, a subsequent statement may modify the initial        statement with a tilde to indicate deletion of the edge from        graph database 200:    -   Edge˜(“Alice”, “ConnectedTo”, “Bob”).

In addition, specific types of edges and/or complex relationships ingraph 210 are defined using schemas 306. Continuing with the previousexample, a schema for employment of a member at a position within acompany is defined using the following:

DefPred(“employ/company”, “1”, “node”, “0”, “node”).DefPred(“employ/member”, “1”, “ node”, “0”, “node”).DefPred(“employ/start”, “1”, “node”, “0”, “date”).DefPred(“employ/end_date”, “1”, “node”, “0”, “date”). M2C@(e, memberId,companyId, start, end) :- Edge(e, “employ/member”, memberId), Edge(e,“employ/company”, companyId), Edge(e, “employ/start”, start), Edge(e,“employ/end_date”, end)

In the above schema, a compound structure for the employment is denotedby the “@” symbol and has a compound type of “M2C.” The compound isrepresented by four predicates and followed by a rule with four edgesthat use the predicates. The predicates include a first predicaterepresenting the employment at the company (e.g., “employ/company”), asecond predicate representing employment of the member (e.g.,“employ/member”), a third predicate representing a start date of theemployment (e.g., “employ/start”), and a fourth predicate representingan end date of the employment (e.g., “employ/end_date”). Each predicateis defined using a corresponding “DefPred” call; the first argument tothe call represents the name of the predicate, the second argument ofthe call represents the cardinality of the subject associated with theedge, the third argument of the call represents the type of subjectassociated with the edge, the fourth argument represents the cardinalityof the object associated with the edge, and the fifth argumentrepresents the type of object associated with the edge.

In the rule, the first edge uses the second predicate to specifyemployment of a member represented by “memberld,” and the second edgeuses the first predicate to specify employment at a company representedby “companyId.” The third edge of the rule uses the third predicate tospecify a “start” date of the employment, and the fourth edge of therule uses the fourth predicate to specify an “end” date of theemployment. All four edges share a common subject denoted by “e,” whichfunctions as a hub node that links the edges to form the compoundrelationship.

In another example, a compound relationship representing endorsement ofa skill in an online professional network includes the following schema:

DefPred(“endorser” , “1”, “node”, “0”, “node”). DefPred(“endorsee”, “1”,“node”, “0”, “node”). DefPred(“skill”, “1”, “node”, “0”, “node”).Endorsements(h, Endorser, Endorsee, Skill) :- Edge(h, “endorser”,Endorser), Edge(h, “endorsee”, Endorsee), Edge(h, “skill”, Skill).

In the above schema, the compound relationship is declared using the “@”symbol and specifies “Endorsement” as a compound type (i.e., data type)for the compound relationship. The compound relationship is representedby three predicates defined as “endorser,” “endorsee,” and “skill.” The“endorser” predicate may represent a member making the endorsement, the“endorsee” predicate may represent a member receiving the endorsement,and the “skill” predicate may represent the skill for which theendorsement is given. The declaration is followed by a rule that mapsthe three predicates to three edges. The first edge uses the firstpredicate to identify the endorser as the value specified in an“Endorser” parameter, the second edge uses the second predicate toidentify the endorsee as the value specified in an “Endorsee” parameter,and the third edge uses the third predicate to specify the skill as thevalue specified in a “Skill” parameter. All three edges share a commonsubject denoted by “h,” which functions as a hub node that links theedges to form the compound relationship. Consequently, the schema maydeclare a ternary relationship for an “Endorsement” compound type, withthe relationship defined by identity-giving attributes with types of“endorser,” “endorsee,” and “skill” and values attached to thecorresponding predicates.

In one or more embodiments, compounds stored in graph database 200 modelcomplex relationships (e.g., employment of a member at a position withina company) using a set of basic types (i.e., binary edges 318) in graphdatabase 200. Each compound represents an n-ary relationship in graph210, with each “component” of the relationship identified using thepredicate and object (or subject) of an edge. A set of “n” edges thatmodel the relationship are then linked to the compound using a commonsubject (or object) that is set to a hub node representing the compound.In turn, new compounds are subsequently dynamically added to graphdatabase 200 without changing the basic types used in graph database200, by specifying relationships that relate the compound structures tothe basic types in schemas 306.

Graph 210 and schemas 306 are used to populate graph database 200 forprocessing queries 308 against the graph. In some embodiments, arepresentation of nodes 316, edges 318, and predicates 320 is obtainedfrom source of truth 334 and stored in a log 312 in the graph database.Lock-free access to graph database 200 is implemented by appendingchanges to graph 210 to the end of the log instead of requiringmodification of existing records in source of truth 334. In turn, graphdatabase 200 provides an in-memory cache of log 312 and an index 314 forefficient and/or flexible querying of the graph.

In some embodiments, nodes 316, edges 318, and predicates 320 are storedas offsets in log 312. For example, the exemplary edge statement forcreating a connection between two members named “Alice” and “Bob” may bestored in a binary log 312 using the following format:

256 Alice 261 Bob 264 ConnectedTo 275 (256, 264, 261)In the above format, each entry in the log is prefaced by a numeric(e.g., integer) offset representing the number of bytes separating theentry from the beginning of the log. The first entry of “Alice” has anoffset of 256, the second entry of “Bob” has an offset of 261, and thethird entry of “ConnectedTo” has an offset of 264. The fourth entry hasan offset of 275 and stores the connection between “Alice” and “Bob” asthe offsets of the previous three entries in the order in which thecorresponding fields are specified in the statement used to create theconnection (i.e., Edge(“Alice”, “ConnectedTo”, “Bob”)).

Because the ordering of changes to graph 210 is preserved in log 312,offsets in log 312 can be used as representations of virtual time ingraph 210. More specifically, each offset represents a different virtualtime in graph 210, and changes in the log up to the offset are used toestablish a state of graph 210 at the virtual time. For example, thesequence of changes from the beginning of log 312 up to a given offsetthat is greater than 0 are applied, in the order in which the changeswere written, to construct a representation of graph 210 at the virtualtime represented by the offset.

Graph database 200 further omits duplication of nodes 316, edges 318,and predicates 320 of graph 210 in log 312. Thus, a node, edge,predicate, and/or other element of graph 210 that has already been addedto log 312 will not be rewritten at a subsequent point in log 312.

Graph database 200 also includes an in-memory index 314 that enablesefficient lookup of edges 318 by subject, predicate, object, and/orother keys or parameters 310. In some embodiments, the index structureincludes one or more hash maps and an edge store. The hash map(s) andedge store are accessed simultaneously by a number of processes,including a single write process and multiple read processes. Entries ineach hash map are accessed using keys or parameters 310 such assubjects, predicates, objects, and/or other linkages that partiallydefine edges in the graph. In turn, each entry in a hash map includes anoffset into a one-linkage structure that stores one additional linkagethat is used to resolve edges associated with the corresponding key oran offset into a two-linkage structure that stores two additionallinkages that are used to resolve edges associated with the key. Edgestore designs for graph database indexes are described in U.S. PatentApplication Publication No. 2018-0144061-A1, entitled “Edge StoreDesigns for Graph Databases” and having filing date 23 Nov. 2016, whichis incorporated herein by reference.

As shown in FIG. 3, a version-management apparatus 302 includesfunctionality to create and maintain multiple versions of graph database200. The versions include a base version 328 of graph database 200 and abranched version 330 that is created from base version 328 at a givenpoint in time. In some embodiments, base version 328 represents a“trunk” of graph database 200 that was created from an empty graphdatabase 200, and branched version 330 represents a “child” of the trunkthat is created as a copy of the trunk at a certain point in time.Alternatively, base version 328 represents a version of graph database200 that is branched off the trunk and/or another previously createdversion of graph database 200, and branched version 330 represents achild of base version 328 that is created as a copy of base version 328at a given point in time. When branched version 330 is created, aseparate copy of log 312 and index 314 are created to store changes tograph 210 in branched version 330 separately from changes made to graph210 in base version 328. Branching of graph databases is described inU.S. Patent Application Publication No. 2017-0212945-A1, entitled“Branchable Graph Databases” and having filing date 21 Jan. 2016, whichis incorporated herein by reference.

In one or more embodiments, version-management apparatus 302 uses a setof operations 322 and data stored in base version 328 and branchedversion 330 to track relationships between nodes 316, edges 318, andpredicates 320 stored in base version 328 and nodes 316, edges 318, andpredicates 320 stored in branched version 330. First, version-managementapparatus 302 stores, in branched version 330, base offsets 324representing the virtual time at which branched version 330 was createdfrom base version 328.

Base offsets 324 include a base offset in log 312 that represents thevirtual time at which branched version 330 was created. For example, thebase offset in log 312 of base version 328 is stored in a header of log312 in branched version 330. As a result, data in log 312 of baseversion 328 up to the base offset can be read by branched version 330,and data in log 312 of branched version 330 is written to offsets thatare after the base offset.

Base offsets 324 also include offsets in the edge store of index 314 inbase version 328 representing the virtual time at which branched version330 was created (e.g., the virtual time that includes changes made tograph database 200 up to the base offset in log 312). For example, thebase offset of a one-linkage structure or two-linkage structure in index314 of base version 328 is stored in the header of one or more portionsof index 314 in branched version 330. As with the base offset in log312, data in index 314 of base version 328, up to base offsets 324 ofthe edge store in base version 328, can be read by branched version 330.Similarly, data in index 314 of branched version 330 is written to edgestore offsets that are after the corresponding base offsets 324.

To allow processing of queries 308 of branched version 330 using data upto base offsets 324 in base version 328, version-management apparatus302 stores references 334 between edge store structures 314 in index 314of branched version 330 and corresponding edge store structures in index314 of base version 328. More specifically, when data is first writtento a one-linkage structure, a two-linkage structure, or another type ofedge store structure in index 314 of branched version 330,version-management apparatus 302 stores a reference from the structureto a corresponding structure in base version 328. For example,management apparatus 302 stores a reference (e.g., pointer, offset,etc.) to a “vlist” structure that stores values of one or more linkagesrelated to a key in base version 328 in the header of a correspondingvlist structure that stores additional values of the linkage(s) relatedto the same key in branched version 330. In turn, a query that readsedges associated with the key in branched version 330 can use thereference to access additional edges associated with the key in thevlist structure of base version 328, up to a base offset in the vlistfrom which branched version 330 was created.

Version-management apparatus 302 also stores references 332-334 andreference types 336-338 that track transitions between “small” and“large” sets of edges in index 314 of both base version 328 and branchedversion 330. As described in U.S. Patent Application Publication No.2018-0144061-A1, two-linkage structures in index 314 store small sets ofedges for a given first linkage value, and one-linkage structures inindex 314 store large sets of edges for a first linkage value byallowing the edge sets to be filtered by the first linkage value and asecond linkage value. Thus, when the number of edges for a first linkagevalue transitions from small to big, storage of the edges in index 314changes from a single two-linkage structure mapped to the first linkagevalue to multiple one-linkage structures mapped to the first linkagevalue and different second linkage values.

In one or more embodiments, version-management apparatus 302, graphdatabase 200, and/or another component of the system write edgesassociated with a given key in branched version 330 to the same type ofedge store structure as edges associated with the same key in baseversion 328. For example, the component identifies a newly written edgein log 312 of branched version 330 and uses the subject in the edge as akey to index 314 in branched version 330. If the key does not exist inbranched version 330, the component searches index 314 in base version328 for the key. If the key exists in base version 328 and maps to atwo-linkage structure that stores a small set of edges for the key, thecomponent creates a corresponding two-linkage structure in branchedversion 330, writes values of the two linkages in the edge to thetwo-linkage structure, and creates a mapping of the key to thetwo-linkage structure in a hash map in branched version 330. If the keyexists in base version 328 and maps to one or more one-linkagestructures that store a large set of edges for the key, the componentcreates a one-linkage structure in branched version 330, writes a valueof the edge's third linkage to the one-linkage structure, and writes avalue of the edge's second linkage to a separate one-linkage structure.The component then creates a mapping of the key and a second linkage inthe edge to the one-linkage structure storing the third linkage valueand a separate mapping of the key to the one-linkage structure storingthe second linkage value. If the key does not exist in base version 328,the component creates a two-linkage structure in branched version 330,writes values of the two linkages in the edge to the two-linkagestructure, and creates a mapping of the key to the two-linkage structurein a hash map in branched version 330.

On the other hand, a small set of edges in either base version 328 orbranched version 330 can become a large set of edges as additional edgeswith the same key are added. When the transition from small to largeoccurs in base version 328 after branched version 330 is created from avirtual time in base version 328 that included a small set of edges forthe key, version-management apparatus 302 performs one or moreoperations 322 that reorganize the edges in a two-linkage structure forthe key into a one-linkage structure that stores values of the secondlinkage in the edges and additional one-linkage structures that storevalues of the third linkage for the key and second linkage value in theedges. Version-management apparatus 302 also creates, in one or morehash maps of base version 328, a mapping of the key to the one-linkagestructure storing the second linkage values and a mapping of the key andeach value of the second linkage to the one-linkage structure storingvalues of the third linkage associated with the key and second linkagevalue. Version-management apparatus 302 also stores a reference from theone-linkage structure that stores values of the second linkage for theedges to the two-linkage structure that stores the original small set ofedges for the key. Version-management apparatus 302 further specifies,in one or more bits stored with the reference, a reference type thatindicates that the reference is from a one-linkage structure for a largeset of edges to a two-linkage structure for an older, smaller set ofedges associated with the same key. As a result, a read of edgesassociated with the key in branched version 330 can use the mapping ofthe key to the one-linkage structure and the reference from theone-linkage structure to the two-linkage structure to access data thatwas written before the virtual time at which branched version 330 wascreated.

When the transition from a small set of edges for a key to a large setof edges for the key occurs in branched version 330 after branchedversion 330 is created from a virtual time in base version 328 thatincluded a small set of edges for the key, version-management apparatus302 performs one or more operations 322 that reorganize the edges in atwo-linkage structure for the key in branched version 330 into aone-linkage structure that stores values of the second linkage in theedges and additional one-linkage structures that store values of thethird linkage for the key and second linkage value in the edges.Version-management apparatus 302 also creates, in one or more hash mapsof branched version 330, a mapping of the key to the one-linkagestructure storing the second linkage values and a mapping of the key andeach value of the second linkage to the one-linkage structure storingvalues of the third linkage associated with the key and second linkagevalue. Version-management apparatus 302 further copies values of thesecond linkage associated with the key from base version 328 to theone-linkage structure storing values of the second linkage in branchedversion 330 and copies values of the third linkage associated with thekey and each second linkage value from base version 330 to thecorresponding one-linkage structures in branched version 330.Version-management apparatus 302 then deletes a reference from thetwo-linkage structure for the key in branched version 330 to thetwo-linkage structure for the key in base version 328. As a result, aread of edges associated with the key in branched version 330 uses theone-linkage structures associated with the key in branched version 330instead of reading from both branched version 330 and base version 328.Version-management apparatus 302 optionally creates a reference from theone-linkage structure that stores values of the second linkage in theedges in branched version 330 to the two-linkage structure for theolder, smaller set of edges for the same key (e.g., in case thetwo-linkage structure needs to be accessed by another branched versionthat is created off branched version 330).

The operation of version-management apparatus is illustrated using theexample base version 328 and branched version 330 of index 314 in FIGS.4A-4B. As shown in FIG. 4A, base version 328 includes a hash map 402that is used to perform lookups of edges by subject (e.g., “S1,” “S2,”“S3”). Base version 328 also includes a hash map 404 that is used toperform lookups of edges by subject and predicate (e.g.., “S3P1,”“S3P2”). As a result, hash map 402 indexes one linkage in edges of baseversion 328, and hash map 402 indexes two linkages in edges of baseversion 320.

The first two entries of hash map 402 (i.e., “S1” and “S2”) map to twodifferent vlists in two-linkage structures 406 in an edge store in baseversion 328. Each vlist contains a linked list of arrays. Within thevlist, a newly allocated page is stored in an array that is doubleand/or another multiple of the size of the previous page, and the headerand/or beginning of the page may point to the end of the previous page.In turn, each vlist in two-linkage structures 406 stores values of thetwo remaining linkages (i.e., predicate and object) in a small set ofedges containing the first linkage value in the corresponding hash map402 entry.

The third entry of hash map 402 (i.e., “S3”) maps to a vlist inone-linkage structures 408 in the edge store of base version 328. Thevlist stores values of a second linkage in a large set of edgescontaining the first linkage value represented by the third entry ofhash map 402. As a result, the vlist is used to partially materialize orresolve edges containing the first linkage value after the number ofedges grows from small to large. More specifically, a lookup of thefirst linkage value in hash map 402 is used to obtain a mapping to thecorresponding vlist in one-linkage structure 408 and materialize one ormore second linkage values in edges with the first linkage value. Thefirst and second linkage values are then used as keys to hash map 404(e.g., “S3P1,” “S3P2”), and mappings of the keys to two different vlistsin a separate set of one-linkage structures 410 in the edge store ofbase version 328 are used to materialize third linkage values in edgescontaining the first and second linkage values.

Branched version 330 is created from base version 328 at a virtual time400 represented by a set of offsets in the vlists of two-linkagestructures 406 and one-linkage structures 408-410. Branched version 330includes a hash map 412 that, like hash map 402 in base version 328, isused to perform lookups of edges by subject (e.g., “S1,” “S2”). Branchedversion 330 also includes a hash map 414 that, like hash map 404 in baseversion 328, is used to perform lookups of edges by subject andpredicate (e.g., “S2P1”). Each entry in hash maps 412-414 indicates theaddition or modification of edges containing the corresponding key inbranched version 330.

The first entry of hash map 412 (i.e., “S1”) maps to a vlist in a set oftwo-linkage structures 416 in the edge store of branched version 330.The vlist stores values of two remaining linkages in a small set ofedges containing the first linkage value represented by the first entryof hash map 412. The vlist also includes a reference 422 to acorresponding vlist for the first linkage value in base version 328. Asa result, a read of edges containing the first linkage value frombranched version 330 is performed by using the vlist in two-linkagestructures 416 to materialize edges containing the first linkage thathave been written to branched version 330, using reference 422 to reachthe corresponding vlist in base version 328, and materializingadditional edges containing the first linkage that have been written tobranched version 330, up to the offset representing virtual time 400.

The second entry of hash map 412 (i.e., “S2”) maps to a vlist in a setof one-linkage structures 418 in the edge store of branched version 330.Like one-linkage structures 408 in base version 328, the vlist inone-linkage structures 418 stores values of a second linkage in a largeset of edges containing the first linkage value represented by thesecond entry of hash map 412. As a result, the vlist is used to identifyvalues of the second linkage in edges containing the first linkagevalue. The first and second linkage values are then used as one or morekeys to hash map 414 (e.g., “S2P1”), and a mapping of each key to avlist in a separate set of one-linkage structures 420 in the edge storeof branched version 338 is used to materialize third linkage values inedges containing the first and second linkage values.

Because the subject of “S2” in branched version includes one or moreentries in hash map 414 that map to one or more vlists in one-linkagestructures 420, the number of edges containing the subject in branchedversion 330 has transitioned from small to large. On the other hand,base version 328 still contains a small set of edges for the samesubject, which is stored in a vlist in two-linkage structures 406 thatis reached via an entry in hash map 402. To reconcile the difference instructures used to store edges for the subject in base version 328 andbranched version 330, values of the second linkage in edges with thesubject are copied from two-linkage structures 406 and 416 to the vlistin one-linkage structures 418, and values of the third linkage in theedges with the subject are copied from two-linkage structures 406 and416 to the vlist in one-linkage structures 420. A reference 424 from thevlist in one-linkage structures 418 to a vlist in two-linkage structures416 that stores the older, small set of edges containing the subject iscreated to allow access to the small set of edges and/or offsetsassociated with the small set of edges in two-linkage structures 416.

As shown in FIG. 4B, base version 328 is also updated after virtual time400. In particular, edges with the subject of “S1” have been added tobase version 328, causing the number of edges containing the subject totransition from small to large. As a result, the first entry in hash map402 maps from the subject to a new vlist in one-linkage structures 408,which is created after virtual time 400 and stores values of a secondlinkage in a large set of edges containing the subject. The subject andsecond linkage values are additionally stored in hash map 404, andmappings from the subject and second linkage values in hash map 404 tovlists created after virtual time 400 in one-linkage structures 410 areused to fully resolve the edges.

To allow reads of edges containing the subject in branched version 330to access data that was written to base version 328 before virtual time400, the vlist in one-linkage structures 408 to which the first entry ofhash map 402 is mapped includes a reference 426 to an older vlist forthe same subject in one-linkage structures 408. After using the firstentry in hash map 402 and reference 426 to access the older vlist, thereads can scan the older vlist until an offset representing virtual time400 is reached. The reads can then retrieve additional edges containingthe subject from the offset and older offsets in the vlist.

As a result, branched versions of the graph database represent variantsor alternative versions of the graph that can be created, modified,and/or deleted without affecting the corresponding base versions. Inturn, the branched versions can be used to perform and validate writesto the graph database before merging the writes into the base version,which improves the integrity of data in the graph database and allowsthe validated writes to be applied in an atomic and consistent mannerThe branched versions can also be used to test changes to the data,schema, and/or querying of the graph database without modifying a sourceof truth for the graph in the base versions, which reduces risk, thepotential for errors or failures, and/or processing overhead associatedwith conventional techniques that deploy changes to the schema, data,and/or querying in databases without testing or validating the changesfirst. Moreover, storing a single copy of data in a base version andusing the data to perform reads of a version that is branched off thebase version reduces the use of storage and/or memory resources in thegraph database. Consequently, the disclosed embodiments providetechnological improvements in applications, tools, computer systems,and/or environments for storing, querying, duplicating, testing,validating, creating, and/or modifying data and/or databases.

Those skilled in the art will appreciate that the system of FIG. 3 maybe implemented in a variety of ways. First, version-management apparatus302, graph database 200, and/or source of truth 334 may be provided by asingle physical machine, multiple computer systems, one or more virtualmachines, a grid, one or more databases, one or more filesystems, and/ora cloud computing system. Version-management apparatus 302, graphdatabase 200, and/or source of truth 334 may additionally be implementedtogether and/or separately by one or more hardware and/or softwarecomponents and/or layers. For example, version-management apparatus 302may be implemented as a process or module that operates within and/orwith graph database 200 and/or using one or more APIs for accessinggraph database 200.

Second, the functionality of the system may be used with other types ofdatabases and/or data. For example, version-management apparatus 302 maysupport branching and/or versioning of relational databases, distributedstreaming platforms, flat files, distributed filesystems, images, audio,video, and/or other types of data.

FIG. 5 shows a flowchart illustrating a process of providing a graphdatabase storing a graph in accordance with the disclosed embodiments.In one or more embodiments, one or more of the steps may be omitted,repeated, and/or performed in a different order. Accordingly, thespecific arrangement of steps shown in FIG. 5 should not be construed aslimiting the scope of the embodiments.

Initially, one or more processes for storing a graph in a base versionof a graph database are executed (operation 502) and used to maintainthe base version of an index of the graph database (operation 504). Forexample, the process(es) include a single write process and multipleread processes. The graph includes a set of edges defined by a firstlinkage, a second linkage, and a third linkage (e.g., a subject,predicate, and object), which are stored in a log-based representationof the graph database. The index includes an edge store containing afirst one-linkage structure storing values of the third linkage, asecond one-linkage structure storing values of the second linkage, and atwo-linkage structure storing values of the second and third linkages.The index also, or instead, includes a first hash map storing mappingsfrom values of the first linkage to the two-linkage structure and thesecond one-linkage structure. The index also, or instead, includes asecond hash map storing mappings from values of the first and secondlinkages to the first one-linkage structure.

Upon branching a version of the graph database from a virtual time inthe base version, a branched version of the index is created fromoffsets corresponding to the virtual time in one-linkage structures andtwo-linkage structures in the base version of the index (operation 506).For example, a base offset of the log is stored as the virtual time atwhich the branched version was created from the base version. Similarly,offsets of each one-linkage structures and two-linkage structure in thebase version that reflect changes up to the base offset in the log arestored as a representation of the virtual time in the index. Changes tothe base version are written to offsets after the virtual time in thelog and index of the base version, and changes to the branched versionare written to offsets after the virtual time in the log and index ofthe branched version.

Finally, the process(es) are used to process queries of the graphdatabase based on the offsets and references from the branched versionof the index to the base version of the index (operation 508). Forexample, a read process performs a read of edges containing a firstlinkage value in the branched version by retrieving a first offset intothe branched version of the edge store from a mapping of the firstlinkage value in a hash map, reading a first subset of edges containingthe first linkage value from the branched version, accessing the baseversion of the edge store using a reference from the branched version tothe base version, and reading a second subset of edges containing thefirst linkage value from the base version.

In another example, the write process performs a write of an edgecontaining values of the first and second linkages that map to the firstone-linkage structure of the base version by writing a value of thethird linkage in the edge to the first one-linkage structure of thebranched version, storing a first reference from the first one-linkagestructure of the branched version to the first one-linkage structure inthe base version that corresponds to the virtual time, and mapping thevalues of the first and second linkages in the second hash map of thebranched version to the first one-linkage structure of the branchedversion. As a result, the write process writes the edge as a part of alarge set of edges in the branched version because the branched versionwas created from the base version that contained a large set of edgeswith the same first linkage value.

In a third example, the process(es) handle an increase in the number ofedges with a given first linkage value in the branched version after thebranched version is created from a virtual time in the base version thatcontained a small set of edges with the first linkage value, asdescribed in further detail below with respect to FIG. 6.

In a fourth example, the process(es) handle an increase in the number ofedges with a given first linkage value in the base version after thebranched version is created from a virtual time in the base version thatcontained a small set of edges with the first linkage value, asdescribed in further detail below with respect to FIG. 7.

FIG. 6 shows a flowchart illustrating the processing of queries of agraph database in accordance with the disclosed embodiments. In one ormore embodiments, one or more of the steps may be omitted, repeated,and/or performed in a different order. Accordingly, the specificarrangement of steps shown in FIG. 6 should not be construed as limitingthe scope of the embodiments.

Initially, a query that writes, to the branched version of the graphdatabase, a first edge containing a first linkage value that maps to thetwo-linkage structure of the base version of the graph database isreceived (operation 602). The query is processed based on a comparisonof the number of edges with the first linkage value after the write ismade with a threshold (operation 604). If the write does not increasethe number of edges with the first linkage value beyond the threshold(e.g., a threshold between a “small” set of edges and a “big” set ofedges), values of the second and third linkages in the first edge arewritten to the two-linkage structure of the branched version (operation606).

Subsequent processing of the query is dependent on whether the query isthe first write of the edge with the first linkage value to the branchedversion (operation 608). If the query is used to write the first newedge with the first linkage value to the branched version (e.g., afterthe branched version is created from a virtual time in the base versionthat contained a small set of edges with the first linkage value), areference from the two-linkage structure of the branched version to thetwo-linkage structure in the base version is stored (operation 610), andthe first linkage value in the first hash map of the branched version ismapped to the two-linkage structure in the branched version (operation612).

If the query writes an edge that increases the number of edges with thefirst linkage value in the branched version beyond the threshold, valuesof the second linkage mapped to the first linkage value in the edge andthe two-linkage structure in the base and branched versions are writtento the second one-linkage structure in the branched version (operation612), and values of the third linkage mapped to the first linkage valuein the edge and the two-linkage structure in the base and branchedversions are written to the first one-linkage structure in the branchedversion (operation 614). In other words, the second and third linkagevalues for the edges are written to structures in the branched versionof the edge store that improve lookup of the large number of edges withthe first linkage value.

The first linkage value is mapped in the first hash map of the branchedversion to the second one-linkage structure in the branched version, andvalues of the first and second linkages in the edge are mapped in thesecond hash map of the branched version to the first one-linkagestructure in the branched version (operation 616). The mapping from thefirst hash map to the second one-linkage structure allows edges with thefirst linkage value to be partially materialized into one or more secondlinkage values. In turn, the first and second linkage values can be usedto retrieve corresponding mappings in the second hash map, which lead toone-linkage structures that store third linkage values in thecorresponding edges.

Finally, a reference from the second one-linkage structure in thebranched version to the two-linkage structure in the branched version isstored (operation 618). The reference allows the older, small set ofedges with the first linkage value to be accessed from the first linkagevalue in the first hash map.

FIG. 7 shows a flowchart illustrating the processing of queries of agraph database in accordance with the disclosed embodiments. In one ormore embodiments, one or more of the steps may be omitted, repeated,and/or performed in a different order. Accordingly, the specificarrangement of steps shown in FIG. 7 should not be construed as limitingthe scope of the embodiments.

Initially, a query that writes an edge that increases the number ofedges with a first linkage value in the base version of the graphdatabase beyond a threshold is received (operation 702). For example,the write of the second edge changes the number of edges with the firstlinkage value from small to large.

Next, values of the second linkage mapped to the first linkage value inthe edge and the two-linkage structure in the base version are writtento the second one-linkage structure in the base version (operation 704),and values of the third linkage mapped to the first linkage value in theedge and the two-linkage structure in the base version are written tothe first one-linkage structure in the base version (operation 706). Inother words, the second and third linkage values for the edges arewritten to structures in the edge store that improve lookup of the largenumber of edges with the first linkage value.

The first linkage value is then mapped in the first hash map of the baseversion to the second one-linkage structure in the base version(operation 708). The mapping from the first hash map to the secondone-linkage structure allows edges with the first linkage value to bepartially materialized into one or more second linkage values. Areference from the second one-linkage structure in the base version tothe two-linkage structure in the base version is also stored (operation710).

A query that reads edges containing the value of the first linkage fromthe branched version is subsequently received (operation 712). Toprocess the query using data from the base version, a lookup of thefirst hash map of the base version is performed to access the secondone-linkage structure in the base version (operation 714), and thereference in the second one-linkage structure is used to access thetwo-linkage structure in the base version (operation 716). Offsets priorto the offset in the two-linkage structure in the base version thatcorresponds to the virtual time at which the branched version wascreated are then scanned for edges containing the value of the firstlinkage (operation 718). As a result, the query is processed in a waythat avoids reading edges written to the base version after the branchedversion is created.

FIG. 8 shows a computer system in accordance with the disclosedembodiments. Computer system 800 includes a processor 802, memory 804,storage 806, and/or other components found in electronic computingdevices. Processor 802 may support parallel processing and/ormulti-threaded operation with other processors in computer system 800.Computer system 800 may also include input/output (I/O) devices such asa keyboard 808, a mouse 810, and a display 812.

Computer system 800 may include functionality to execute variouscomponents of the present embodiments. In particular, computer system800 may include an operating system (not shown) that coordinates the useof hardware and software resources on computer system 800, as well asone or more applications that perform specialized tasks for the user. Toperform tasks for the user, applications may obtain the use of hardwareresources on computer system 800 from the operating system, as well asinteract with the user through a hardware and/or software frameworkprovided by the operating system.

In one or more embodiments, computer system 800 provides a system forproviding a graph database. The system includes a set of processes,which may include a single write process and multiple read processes.The processes maintain the base version of an index of the graphdatabase. Upon branching a version of the graph database from a firstoffset representing a virtual time in the base version of the graphdatabase, the processes create a branched version of the index from asecond offset corresponding to the virtual time in the base version ofthe index. The processes then process queries of the graph databasebased on the offsets and references from the branched version of theindex to the base version of the index.

In addition, one or more components of computer system 800 may beremotely located and connected to the other components over a network.Portions of the present embodiments (e.g., version-management apparatus,graph database, source of truth, processes, etc.) may also be located ondifferent nodes of a distributed system that implements the embodiments.For example, the present embodiments may be implemented using a cloudcomputing system that manages and/or maintains branched and baseversions of a remote graph database.

The data structures and code described in this detailed description aretypically stored on a computer-readable storage medium, which may be anydevice or medium that can store code and/or data for use by a computersystem. The computer-readable storage medium includes, but is notlimited to, volatile memory, non-volatile memory, magnetic and opticalstorage devices such as disk drives, magnetic tape, CDs (compact discs),DVDs (digital versatile discs or digital video discs), or other mediacapable of storing code and/or data now known or later developed.

The methods and processes described in the detailed description sectioncan be embodied as code and/or data, which can be stored in acomputer-readable storage medium as described above. When a computersystem reads and executes the code and/or data stored on thecomputer-readable storage medium, the computer system performs themethods and processes embodied as data structures and code and storedwithin the computer-readable storage medium.

Furthermore, methods and processes described herein can be included inhardware modules or apparatus. These modules or apparatus may include,but are not limited to, an application-specific integrated circuit(ASIC) chip, a field-programmable gate array (FPGA), a dedicated orshared processor (including a dedicated or shared processor core) thatexecutes a particular software module or a piece of code at a particulartime, and/or other programmable-logic devices now known or laterdeveloped. When the hardware modules or apparatus are activated, theyperform the methods and processes included within them.

The foregoing descriptions of various embodiments have been presentedonly for purposes of illustration and description. They are not intendedto be exhaustive or to limit the present invention to the formsdisclosed. Accordingly, many modifications and variations will beapparent to practitioners skilled in the art. Additionally, the abovedisclosure is not intended to limit the present invention.

What is claimed is:
 1. A method, comprising: executing one or moreprocesses for storing a graph in a base version of a graph database,wherein the graph comprises a set of edges defined by a first linkage, asecond linkage, and a third linkage; maintaining, by the one or moreprocesses, the base version of an index of the graph database, whereinthe index comprises: an edge store comprising a first one-linkagestructure storing values of the third linkage, a second one-linkagestructure storing values of the second linkage, and a two-linkagestructure storing values of the second and third linkages; a first hashmap storing mappings from values of the first linkage to the two-linkagestructure and the second one-linkage structure; and a second hash mapstoring mappings from the values of the first and second linkages to thefirst one-linkage structure; upon branching a version of the graphdatabase from a virtual time in the base version of the graph database,creating, by the one or more processes, a branched version of the indexfrom offsets corresponding to the virtual time in the first and secondone-linkage structures and the two-linkage structure in the base versionof the index; and using the one or more processes to process queries ofthe graph database based on the offsets and references from the branchedversion of the index to the base version of the index.
 2. The method ofclaim 1, wherein using the one or more processes to process the queriesof the graph database comprises: when a first query of the branchedversion comprises a write of a first edge comprising a value of thefirst linkage that maps to the two-linkage structure of the baseversion: writing values of the second and third linkages in the firstedge to the two-linkage structure of the branched version; and storing afirst reference from the two-linkage structure of the branched versionto the two-linkage structure in the base version.
 3. The method of claim2, wherein using the one or more processes to process the queries of thegraph database further comprises: mapping the value of the first linkagein the first hash map of the branched version to the two-linkagestructure in the branched version.
 4. The method of claim 2, whereinusing the one or more processes to process the queries of the graphdatabase further comprises: when a second query of the branched versioncomprises a write of a second edge that increases a number of edgescomprising the value of the first linkage in the branched version beyonda threshold: writing values of the second linkage mapped to the value ofthe first linkage in the second edge and the two-linkage structure inthe base version and the branched version to the second one-linkagestructure in the branched version; writing values of the third linkagemapped to the value of the first linkage in the second edge and thetwo-linkage structure in the base version and the branched version tothe first one-linkage structure in the branched version; and mapping thevalue of the first linkage in the first hash map of the branched versionto the second one-linkage structure in the branched version.
 5. Themethod of claim 4, wherein using the one or more processes to processthe queries of the graph database further comprises: storing a secondreference from the second one-linkage structure in the branched versionto the two-linkage structure in the branched version.
 6. The method ofclaim 4, wherein using the one or more processes to process the queriesof the graph database further comprises: mapping the value of the firstlinkage and the value of the second linkage in the second edge in thesecond hash map of the branched version to the first one-linkagestructure in the branched version.
 7. The method of claim 1, whereinusing the one or more processes to process the queries of the graphdatabase comprises: when a first query of the base version comprises awrite of an edge that increases a number of edges comprising a value ofthe first linkage in the base version beyond a threshold: writing valuesof the second linkage mapped to the value of the first linkage in theedge and the two-linkage structure in the base version to the secondone-linkage structure in the base version; writing values of the thirdlinkage mapped to the value of the first linkage in the edge and thetwo-linkage structure in the base version to the first one-linkagestructure in the base version; mapping the value of the first linkage inthe first hash map of the base version to the second one-linkagestructure in the base version; and storing a reference from the secondone-linkage structure in the base version to the two-linkage structurein the base version.
 8. The method of claim 7, wherein using the one ormore processes to process the queries of the graph database furthercomprises: when a second query of the branched version comprises a readof edges comprising the value of the first linkage: performing a lookupof the first hash map of the base version to access the secondone-linkage structure in the base version; using the reference in thesecond one-linkage structure to access the two-linkage structure in thebase version; and scanning offsets prior to an offset of the two-linkagestructure in the base version that corresponds to the virtual time forthe edges comprising the value of the first linkage.
 9. The method ofclaim 1, wherein using the one or more processes to process the queriesof the graph database comprises: when a first query of the branchedversion comprises a write of an edge comprising values of the first andsecond linkages that map to the first one-linkage structure of the baseversion: writing a value of the third linkage in the edge to the firstone-linkage structure of the branched version; and storing a firstreference from the first one-linkage structure of the branched versionto the first one-linkage structure in the base version that correspondsto the virtual time.
 10. The method of claim 9, wherein using the one ormore processes to process the queries of the graph database furthercomprises: mapping the values of the first and second linkages in thesecond hash map of the branched version to in the first one-linkagestructure of the branched version.
 11. The method of claim 1, whereinusing the one or more processes to process the queries of the graphdatabase comprises: when a query of the branched version comprises aread of edges comprising a value of the first linkage: retrieving afirst offset into the branched version of the edge store from a mappingof the value of the first linkage in the first or second hash maps;reading a first subset of edges comprising the value of the firstlinkage from the branched version; accessing the base version of theedge store based on a reference from the branched version to the baseversion; and reading a second subset of edges comprising the value ofthe first linkage from the base version.
 12. The method of claim 1,wherein the first, second, and third linkages comprise: a subject; apredicate; and an object.
 13. A system, comprising: one or moreprocessors; and memory storing instructions that, when executed by theone or more processors, cause the system to: store a graph in a baseversion of a graph database, wherein the graph comprises a set of edgesdefined by a first linkage, a second linkage, and a third linkage;maintain the base version of an index of the graph database, wherein theindex comprises: an edge store comprising a first one-linkage structurestoring values of the third linkage, a second one-linkage structurestoring values of the second linkage, and a two-linkage structurestoring values of the second and third linkages; a first hash mapstoring mappings from values of the first linkage to the two-linkagestructure and the second one-linkage structure; and a second hash mapstoring mappings from values of the first and second linkages to thefirst one-linkage structure; upon branching a version of the graphdatabase from a virtual time in the base version of the graph database,create a branched version of the index from offsets corresponding to thevirtual time in the first and second one-linkage structures and thetwo-linkage structure in the base version of the index; and processqueries of the graph database based on the offsets and references fromthe branched version of the index to the base version of the index. 14.The system of claim 13, wherein processing the queries of the graphdatabase comprises: when a first query of the branched version comprisesa write of a first edge comprising a value of the first linkage thatmaps to the two-linkage structure of the base version: writing values ofthe second and third linkages in the first edge to the two-linkagestructure of the branched version; storing a first reference from thetwo-linkage structure of the branched version to the two-linkagestructure in the base version; and mapping the value of the firstlinkage in the first hash map of the branched version to the two-linkagestructure in the branched version.
 15. The system of claim 14, whereinprocessing the queries of the graph database further comprises: when asecond query of the branched version comprises a write of a second edgethat increases a number of edges comprising the value of the firstlinkage in the branched version beyond a threshold: writing values ofthe second linkage mapped to the value of the first linkage in thesecond edge and the two-linkage structure in the base version and thebranched version to the second one-linkage structure in the branchedversion; writing values of the third linkage mapped to the value of thefirst linkage in the second edge and the two-linkage structure in thebase version and the branched version to the first one-linkage structurein the branched version; and mapping the value of the first linkage inthe first hash map of the branched version to the second one-linkagestructure in the branched version.
 16. The system of claim 15, whereinprocessing the queries of the graph database further comprises: storinga second reference from the second one-linkage structure in the branchedversion to the two-linkage structure in the branched version; andmapping the value of the first linkage and the value of the secondlinkage in the second edge in the second hash map of the branchedversion to the first one-linkage structure in the branched version. 17.The system of claim 13, wherein processing the queries of the graphdatabase comprises: when a first query of the base version comprises awrite of an edge that increases a number of edges comprising a value ofthe first linkage in the base version beyond a threshold: writing valuesof the second linkage mapped to the value of the first linkage in theedge and the two-linkage structure in the base version to the secondone-linkage structure in the base version; writing values of the thirdlinkage mapped to the value of the first linkage in the edge and thetwo-linkage structure in the base version to the first one-linkagestructure in the base version; mapping the value of the first linkage inthe first hash map of the base version to the second one-linkagestructure in the base version; and storing a reference from the secondone-linkage structure in the base version to the two-linkage structurein the base version.
 18. The system of claim 17, wherein processing thequeries of the graph database further comprises: when a second query ofthe branched version comprises a read of edges comprising the value ofthe first linkage: performing a lookup of the first hash map of the baseversion to access the second one-linkage structure in the base version;using the reference in the second one-linkage structure to access thetwo-linkage structure in the base version; and scanning offsets prior toan offset of the two-linkage structure in the base version thatcorresponds to the virtual time for the edges comprising the value ofthe first linkage.
 19. The system of claim 13, wherein the first,second, and third linkages comprise: a subject; a predicate; and anobject.
 20. A non-transitory computer-readable storage medium storinginstructions that when executed by a computer cause the computer toperform a method, the method comprising: executing one or more processesfor storing a graph in a base version of a graph database, wherein thegraph comprises a set of edges defined by a first linkage, a secondlinkage, and a third linkage; maintaining, by the one or more processes,the base version of an index of the graph database; upon branching aversion of the graph database from a first offset representing a virtualtime in the base version of the graph database, creating, by the one ormore processes, a branched version of the index from a second offsetcorresponding to the virtual time in the base version of the index; andusing the one or more processes to process queries of the graph databasebased on the first and second offsets and references from the branchedversion of the index to the base version of the index.